def test_is_fixed(self):
p = parameter()
self.assertEqual(p.is_fixed(), True)
self.assertEqual(is_fixed(p), True)
p.value = 1.0
self.assertEqual(p.is_fixed(), True)
self.assertEqual(is_fixed(p), True)
def test_is_fixed(self):
v = variable()
self.assertEqual(v.is_fixed(), False)
self.assertEqual(is_fixed(v), False)
self.assertEqual(v.fixed, False)
self.assertEqual(v.value, None)
v.value = 1.0
self.assertEqual(v.is_fixed(), False)
self.assertEqual(is_fixed(v), False)
self.assertEqual(v.fixed, False)
self.assertEqual(v.value, 1.0)
v.fix()
self.assertEqual(v.is_fixed(), True)
self.assertEqual(is_fixed(v), True)
self.assertEqual(v.fixed, True)
self.assertEqual(v.value, 1.0)
v.value = None
self.assertEqual(v.is_fixed(), True)
self.assertEqual(is_fixed(v), True)
self.assertEqual(v.fixed, True)
self.assertEqual(v.value, None)
v.free()
self.assertEqual(v.is_fixed(), False)
self.assertEqual(is_fixed(v), False)
self.assertEqual(v.fixed, False)
self.assertEqual(v.value, None)
def test_is_fixed(self):
v = variable()
e = noclone(v + 1)
self.assertEqual(e.is_fixed(), False)
self.assertEqual(is_fixed(e), False)
v.fix()
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
e = noclone(parameter())
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
def test_is_fixed(self):
e = self._ctype_factory()
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
e.expr = 1
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
v = variable()
v.value = 2
e.expr = v + 1
self.assertEqual(e.is_fixed(), False)
self.assertEqual(is_fixed(e), False)
v.fix()
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
self.assertEqual(e(), 3)
def test_is_fixed(self):
e = self._ctype_factory()
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
e.expr = 1
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
p = parameter()
e.expr = p**2
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
a = self._ctype_factory()
e.expr = (a * p)**2 / (p + 5)
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
a.expr = 2.0
p.value = 5.0
self.assertEqual(e.is_fixed(), True)
self.assertEqual(is_fixed(e), True)
self.assertEqual(e(), 10.0)
v = variable()
with self.assertRaises(ValueError):
e.expr = v + 1
def _add_constraint(self, con):
if not con.active:
return None
if is_fixed(con.body):
if self._skip_trivial_constraints:
return None
conname = self._symbol_map.getSymbol(con, self._labeler)
if con._linear_canonical_form:
gurobi_expr, referenced_vars = self._get_expr_from_pyomo_repn(
con.canonical_form(), self._max_constraint_degree)
elif isinstance(con, LinearCanonicalRepn):
gurobi_expr, referenced_vars = self._get_expr_from_pyomo_repn(
con, self._max_constraint_degree)
else:
gurobi_expr, referenced_vars = self._get_expr_from_pyomo_expr(
con.body, self._max_constraint_degree)
if con.has_lb():
if not is_fixed(con.lower):
raise ValueError(
'Lower bound of constraint {0} is not constant.'.format(
con))
if con.has_ub():
if not is_fixed(con.upper):
raise ValueError(
'Upper bound of constraint {0} is not constant.'.format(
con))
if con.equality:
gurobipy_con = self._solver_model.addConstr(
lhs=gurobi_expr,
sense=self._gurobipy.GRB.EQUAL,
rhs=value(con.lower),
name=conname)
elif con.has_lb() and (value(con.lower) >
-float('inf')) and con.has_ub() and (value(
con.upper) < float('inf')):
gurobipy_con = self._solver_model.addRange(gurobi_expr,
value(con.lower),
value(con.upper),
name=conname)
self._range_constraints.add(con)
elif con.has_lb() and (value(con.lower) > -float('inf')):
gurobipy_con = self._solver_model.addConstr(
lhs=gurobi_expr,
sense=self._gurobipy.GRB.GREATER_EQUAL,
rhs=value(con.lower),
name=conname)
elif con.has_ub() and (value(con.upper) < float('inf')):
gurobipy_con = self._solver_model.addConstr(
lhs=gurobi_expr,
sense=self._gurobipy.GRB.LESS_EQUAL,
rhs=value(con.upper),
name=conname)
else:
raise ValueError(
'Constraint does not have a lower or an upper bound: {0} \n'.
format(con))
for var in referenced_vars:
self._referenced_variables[var] += 1
self._vars_referenced_by_con[con] = referenced_vars
self._pyomo_con_to_solver_con_map[con] = gurobipy_con
self._solver_con_to_pyomo_con_map[gurobipy_con] = con
def _add_constraint(self, con):
if not con.active:
return None
if is_fixed(con.body):
if self._skip_trivial_constraints:
return None
conname = self._symbol_map.getSymbol(con, self._labeler)
if con._linear_canonical_form:
cplex_expr, referenced_vars = self._get_expr_from_pyomo_repn(
con.canonical_form(), self._max_constraint_degree)
elif isinstance(con, LinearCanonicalRepn):
cplex_expr, referenced_vars = self._get_expr_from_pyomo_repn(
con, self._max_constraint_degree)
else:
cplex_expr, referenced_vars = self._get_expr_from_pyomo_expr(
con.body, self._max_constraint_degree)
if con.has_lb():
if not is_fixed(con.lower):
raise ValueError(
'Lower bound of constraint {0} is not constant.'.format(
con))
if con.has_ub():
if not is_fixed(con.upper):
raise ValueError(
'Upper bound of constraint {0} is not constant.'.format(
con))
if con.equality:
my_sense = 'E'
my_rhs = [value(con.lower) - cplex_expr.offset]
my_range = []
elif con.has_lb() and (value(con.lower) >
-float('inf')) and con.has_ub() and (value(
con.upper) < float('inf')):
my_sense = 'R'
lb = value(con.lower)
ub = value(con.upper)
my_rhs = [ub - cplex_expr.offset]
my_range = [lb - ub]
self._range_constraints.add(con)
elif con.has_lb() and (value(con.lower) > -float('inf')):
my_sense = 'G'
my_rhs = [value(con.lower) - cplex_expr.offset]
my_range = []
elif con.has_ub() and (value(con.upper) < float('inf')):
my_sense = 'L'
my_rhs = [value(con.upper) - cplex_expr.offset]
my_range = []
else:
raise ValueError(
'Constraint does not have a lower or an upper bound: {0} \n'.
format(con))
if len(cplex_expr.q_coefficients) == 0:
self._solver_model.linear_constraints.add(
lin_expr=[[cplex_expr.variables, cplex_expr.coefficients]],
senses=my_sense,
rhs=my_rhs,
range_values=my_range,
names=[conname])
else:
if my_sense == 'R':
raise ValueError(
'The CPLEXDirect interface does not support quadratic ' +
'range constraints: {0}'.format(con))
self._solver_model.quadratic_constraints.add(
lin_expr=[cplex_expr.variables, cplex_expr.coefficients],
quad_expr=[
cplex_expr.q_variables1, cplex_expr.q_variables2,
cplex_expr.q_coefficients
],
sense=my_sense,
rhs=my_rhs[0],
name=conname)
for var in referenced_vars:
self._referenced_variables[var] += 1
self._vars_referenced_by_con[con] = referenced_vars
self._pyomo_con_to_solver_con_map[con] = conname
self._solver_con_to_pyomo_con_map[conname] = con
def _get_bound(exp):
if exp is None:
return None
if is_fixed(exp):
return value(exp)
raise ValueError("non-fixed bound or weight: " + str(exp))
def is_fixed(self):
"""A boolean indicating whether this expression is fixed."""
return is_fixed(self._expr)
